US5596367A - Averaging green values for green photosites in electronic cameras - Google Patents
Averaging green values for green photosites in electronic cameras Download PDFInfo
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- US5596367A US5596367A US08/606,178 US60617896A US5596367A US 5596367 A US5596367 A US 5596367A US 60617896 A US60617896 A US 60617896A US 5596367 A US5596367 A US 5596367A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
- H04N23/84—Camera processing pipelines; Components thereof for processing colour signals
- H04N23/843—Demosaicing, e.g. interpolating colour pixel values
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N2209/00—Details of colour television systems
- H04N2209/04—Picture signal generators
- H04N2209/041—Picture signal generators using solid-state devices
- H04N2209/042—Picture signal generators using solid-state devices having a single pick-up sensor
- H04N2209/045—Picture signal generators using solid-state devices having a single pick-up sensor using mosaic colour filter
- H04N2209/046—Colour interpolation to calculate the missing colour values
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/10—Circuitry of solid-state image sensors [SSIS]; Control thereof for transforming different wavelengths into image signals
- H04N25/11—Arrangement of colour filter arrays [CFA]; Filter mosaics
- H04N25/13—Arrangement of colour filter arrays [CFA]; Filter mosaics characterised by the spectral characteristics of the filter elements
- H04N25/134—Arrangement of colour filter arrays [CFA]; Filter mosaics characterised by the spectral characteristics of the filter elements based on three different wavelength filter elements
Definitions
- This invention relates to the field of electronic imaging and more particularly to providing improved green pixel values.
- the object of this invention is to provide an improved apparatus for reducing noise in the green pixel values in a CFA.
- apparatus for processing a digitized image signal obtained from an image sensor having red, green, and blue color photosites aligned in rows and columns that generate at least three separate color values but only one color value for each photosite location means for averaging existing green pixel values for green photosite locations comprising:
- means for modifying a measured green pixel value based upon adjacent pixel classifier values including:
- (ii) means for replacing the measured green pixel values for a green photosite location with an average of surrounding predicted green pixel values as a function of the number of classifiers which are below a predetermined value.
- the advantages of this invention are 1) is computationally efficient both in execution time and memory storage requirements; and 2) by use of the combination of the Laplacian second-order values and gradient values to produce a classifier, and use of averaging to produce a predictor, noise in green pixel values is substantially reduced.
- FIG. 1 is a block diagram of an electronic still camera employing interpolation processing according to the invention
- FIG. 2 is a block diagram of the logic of the interpolation and averaging processing techniques used in connection with the invention
- FIG. 3 is a detailed block diagram of the logic of the interpolation luminance section in FIG. 2;
- FIG. 4 is a more detailed block diagram of the logic of the chrominance section in FIG. 2;
- FIGS. 5 and 6 show logic block diagrams for the interpolation processes in accordance with the invention.
- FIG. 7 is a detailed block diagram of the logic of luminance averaging section in FIG. 2.
- an electronic still camera is divided generally into an input section 2 and an interpolation and recording section 4.
- the input section 2 includes an exposure section 10 for directing image light from a subject (not shown) toward an image sensor 12.
- the exposure section 10 includes conventional optics for directing the image light through a diaphragm, which regulates the optical aperture, and a shutter, which regulates exposure time.
- the image sensor 12, which includes a two-dimensional array of photosites corresponding to picture elements of the image, is a conventional charge-coupled device (CCD) using either well-known interline transfer or frame transfer techniques.
- CCD charge-coupled device
- the image sensor 12 is covered by a color filter array (CFA) 13, known as the Bayer array, which is described in U.S. Pat. No.
- CFA color filter array
- each color covers a photosite, or picture element (pixel), of the sensor.
- chrominance colors red and blue
- luminance colors green
- the image sensor 12 is exposed to image light so that analog image charge information is generated in respective photosites.
- the charge information is applied to an output diode 14, which converts the charge information to analog image signals corresponding to respective picture elements.
- the analog image signals are applied to an A/D converter 16, which generates a digital image signal from the analog input signal for each picture element.
- the digital signals are applied to an image buffer 18, which may be a random access memory (RAM) with storage capacity for a plurality of still images.
- RAM random access memory
- a control processor 20 generally controls the input section 2 of the camera by initiating and controlling exposure (by operation by the diaphragm and shutter (not shown) in the exposure section 10), by generating the horizontal and vertical clocks needed for driving the image sensor 12 and for clocking image information therefrom, and by enabling the A/D converter 16 in conjunction with the image buffer 18 for each signal segment relating to a picture element.
- the control processor 20 would ordinarily include a microprocessor coupled with a system timing circuit.
- the stored signals are applied to a digital signal processor 22, which controls the throughput processing rate for the interpolation and recording section 4 of the camera.
- the digital signal processor 22 applies an interpolation algorithm to the digital image signals, and sends the interpolated signals to a conventional, removable memory card 24 via a connector 26.
- the intermediate products of the processing algorithm are stored in a processing buffer 28.
- the processing buffer 28 may also be configured as part of the memory space of the image buffer 18.
- the number of image signals needed in the image buffer 18 before digital processing can begin depends on the type of processing, that is, for a neighborhood interpolation to begin, a block of signals including at least a portion of the image signals comprising a video frame must be available. Consequently, in most circumstances, the interpolation may commence as soon as the requisite block of picture elements is present in the buffer 18.
- the input section 2 operates at a rate commensurate with normal operation of the camera while interpolation, which may consume more time, can be relatively divorced from the input rate.
- the exposure section 10 exposes the image sensor 12 to image light for a time period dependent upon exposure requirements, for example, a time period between 1/1000 second and several seconds.
- the image charge is then swept from the photosites in the image sensor 12, converted to a digital format, and written into the image buffer 18.
- the driving signals provided by the control processor 20 to the image sensor 12, the A/D converter 16 and the buffer 18 are accordingly generated to achieve such a transfer.
- the processing throughput rate of the interpolation and recording section 4 is determined by the speed of the digital signal processor 22.
- the processing algorithm employed in the interpolation and recording section may be selected for quality treatment of the image rather than for throughput speed.
- This can put a delay between consecutive pictures which may affect the user, depending on the time between photographic events.
- This is a problem since it is well known and understood in the field of electronic imaging that a digital still camera should provide a continuous shooting capability for a successive sequence of images.
- the image buffer 18 shown in FIG. 1 provides for storage of a plurality of images, in effect allowing a series of images to "stack up" at video rates. The size of the buffer is established to hold enough consecutive images to cover most picture-taking situations.
- An operation display panel 30 is connected to the control processor 20 for displaying information useful in operation of the camera.
- information useful in operation of the camera might include typical photographic data, such as shutter speed, aperture, exposure bias, color balance (auto, tungsten, fluorescent, daylight), field/frame, low battery, low light, exposure modes (aperture preferred, shutter preferred), and so on.
- other information unique to this type of camera is displayed.
- the removable memory card 24 would ordinarily include a directory signifying the beginning and ending of each stored image. This would show on the display panel 30 as either (or both) the number of images stored or the number of image spaces remaining, or estimated to be remaining.
- the digital signal processor 22 interpolates each still video image stored in the image buffer 18 according to the interpolation technique shown in FIG. 2.
- the interpolation of missing data values at each pixel location follows the sequence shown in FIG. 2; that is, first, the high frequency information for the "missing green" pixels (i.e., the red and blue pixel locations) are interpolated to improve the luminance rendition. The resulting luminance values are then averaged to reduce noise in the luminance values. Finally, the color difference information is interpolated at the high frequency locations by bilinear methods to generate the other colors of the CFA pattern.
- an adaptive interpolation technique is used in the luminance section 36 for optimizing the performance of the system for images with horizontal and vertical edges.
- “Missing green” pixels are adaptively interpolated either horizontally, vertically or two-dimensionally depending upon the gradients, Laplacian second-order values and color difference bias values established from the neighboring pixel locations in the vertical and horizontal directions around the "missing green” pixel.
- the first step for adaptively interpolating the "missing green” pixels is to select an interpolation method.
- the details of this process are shown in block 40 of FIG. 3.
- the process starts by computing two composite pixel classifier values in block 50, one for the horizontal direction and one for the vertical.
- pixel classifier denotes a value computed for the purpose of making a decision about further processing of the pixel information.
- composite denotes the dependency of the value on a multiplicity of color planes.
- the two classifier values are compared in block 51 versus a predetermined value hereinafter referred to as "the first threshold value”. If both classifier values are less than the first threshold value, then the interpolation method corresponding to slowly changing scene detail is selected in block 52. "Slowly changing scene detail" means both horizontal direction classifier value and vertical direction classifier value are less than the first threshold value. If at least one of the classifier values is greater than or equal to the first threshold value, both classifier values are compared in block 53 to a predetermined value hereinafter referred to as "the second threshold value”. If both classifier values are greater than the second threshold value, then the interpolation method corresponding to rapidly changing scene detail is selected in block 54.
- Rapidly changing scene detail means both horizontal direction classifier value and vertical direction classifier value are greater than the second threshold value. If at least one of the classifier values is less than or equal to the second threshold value, then the classifier values are compared in block 55 to each other. In the likely event that one of the classifier values is less than the other classifier value, the interpolation method corresponding to the smaller classifier value in block 57 is chosen. If both classifier values are equal in value, then the default interpolation method in block 56 is chosen. At this point block 40 is complete.
- the green (luma) interpolation step in block 44 has two parts, as shown in FIG. 4.
- the first part in block 80 averages the two luminance (green) values according to the selected interpolation method.
- the second part in block 82 adds a correction factor based on either red or blue neighboring values depending on if the pixel in question was covered by a red or blue filter in the Bayer color filter array and the interpolation method selected by block 40.
- the green (luma) pixel value averaging step is block 32 has two parts, as shown in FIG. 2.
- the process begins by selecting which green pixel values to average in block 42.
- the details of block 42 are shown in FIG. 7.
- the process begins by calculating the horizontal and vertical composite classifier values for each green pixel horizontally or vertically adjacent to the green pixel in question in block 90.
- the term "composite” denotes the dependency of the value on a multiplicity of planes. In this case the absolute value of the Laplacian second-order value of the red or blue plane, depending on which was the corresponding color in the Bayer color filter array, is added to the absolute value of the gradient of the green plane.
- the absolute value of the color difference bias value may also be added to the classifier value, but it need not be.
- the classifier values of the adjacent green pixels are compared to a predetermined value hereinafter referred to as the "threshold value". In another embodiment of this invention this threshold value would be identical to the previously defined “first threshold value", though it need not be. If two or more adjacent green pixels have both their classifier values less than the threshold value, then the green pixel in question is selected for averaging in block 94. This completes block 42.
- block 43 the selected green pixel values are replaced with the average of the horizontally and vertically adjacent green pixel values. This completes block 32.
- the red/blue (chroma) interpolation proceeds in a manner similar to the green (luma) interpolation described above.
- the details of this process are shown in Block 46 of FIG. 5.
- the process starts by determining if the two horizontally adjacent pixels to the pixel with the "missing" chroma value in question (either red or blue) are of the same color as the missing chroma value in block 60. If the two horizontally adjacent pixel values are the correct color, then the horizontal interpolation method in block 61 is used. If the two vertically adjacent pixels are of the same color as the "missing" chroma value in block 62, then the vertical interpolation method in block 63 is chosen.
- the two classifier values are then compared in block 65 and tested for equality. In the likely event that one value is smaller than the other, the interpolation method corresponding to the smaller value is selected in block 67. If the values are equal, then the default interpolation method is selected in block 66. At this point Block 46 is done.
- the red/blue (chroma) interpolation step in block 48 has two parts, as shown in FIG. 6.
- first part in block 70 two chrominance values, either red or blue depending on the pixel's position in the Bayer color filter array, are averaged according to the selected interpolation method.
- the second part in block 72 adds a correction factor based on green neighboring values.
- the first pass of the interpolation fully populates the green color plane.
- the Bayer color filter array is assumed. Consider the following pixel neighborhood.
- Gx is a green pixel and Ax is either a red pixel or a blue pixel. (All Ax pixels will be the same color for the entire neighborhood.) For simplicity, we will use the term "chroma" to mean either red or blue.
- classifiers We form the following classifiers.
- bh' is the previous value of bh along the same row
- bv' is the previous value of bv along the same column
- G1' and G3' are previously predicted green values. Both bh and bv are initialized to zero at the beginning of the row/column. (Note that as the algorithm is usually implemented to process the image row by row, bh can be a simple variable and bv is a one-dimensional array with an entry for each column). Note that Ax is either Rx or Bx. (All Ax's will be the same color).
- These classifiers are composed of Laplacian second-order values for the chroma data, gradient values for the green data and color difference bias values that use both chroma and green data.
- -A3+2A5-A7 is a Laplacian second-order value
- G4-G6 is a green gradient value
- -G5+2(A5+bh)-G6 is a color difference bias value.
- these classifiers are sensing the high spatial frequency information present in the pixel neighborhood in the horizontal (h) and vertical (v) directions.
- predictors are composed of arithmetic averages for the green data and, in the case of F, H and V, appropriately scaled Laplacian second-order values for the chroma data.
- Predictor A is to be used when both horizontal and vertical classifier values are less than the first threshold value, T1.
- T1 is chosen to reduce noise in the image reconstruction in regions of slowly changing scene detail.
- An appropriate value for T1 is 25 when the green pixel values and chroma pixel values range from 0 to 255.
- Predictor F is used when both horizontal and vertical classifier values are greater than the second threshold value, T2.
- T2 is chosen to reduce noise in the image reconstruction in regions of rapidly changing scene detail.
- T2 An appropriate value for T2 is 200 when the green pixel values and chroma pixel values range from 0 to 255.
- Predictor H is to be used when the preferred orientation for the interpolation is in the horizontal direction within the pixel neighborhood.
- predictor V is to be used when the preferred orientation for the interpolation is the vertical direction.
- both the green and the chroma data must indicate a minimum of high spatial frequency information for a given orientation to be chosen as the preferred orientation for the interpolation. If there is a large amount of high spatial frequency information in either the green data or chroma data for a given orientation, it will inflate the value of the corresponding classifier. This, in turn, reduces the likelihood for that orientation to be chosen as the preferred orientation for the interpolation.
- Gx is an original green pixel value and Gx' is a predicted green pixel value. If two or more of the Gx' values were interpolated using the method corresponding to slowly changing scene detail, then Gx is replaced with the following value, G5":
- G5" when two or more values of Gx' were predicted using predictor A. This need not be, however, as any method of interpolation appropriate to slowly changing scene detail could be used in place of predictor A. (Note that if all four predicted values were derived using predictor A, then G5" becomes, equivalently:
- G7 is a center weighted average.
- Gx is a green pixel
- Ax is either a red or blue pixel
- C5 is the opposite color pixel to Ax (i.e., if Ax is red then C5 is blue and visa versa). Note that all Gx pixels, G1 through G9, are assumed to be known and coincident with all corresponding Ax and C5 pixels.
- Case 1 is when the nearest same colored neighbors to Ax are in the same column.
- the following predictor is used. (A4 is used as an example.)
- Case 2 is when the nearest same colored neighbors to Ax are in the same row.
- the following predictor is used. (A2 is used as an example.)
- Case 3 is when the nearest same colored neighbors to Ax are at the four corners.
- the following predictor is used. (A5 is used as an example.)
- These classifiers are composed of Laplacian second-order values for the green data and gradient values for the chroma data. As such, these classifiers are sensing the high spatial frequency information present in the pixel neighborhood in the negative diagonal (DN) and positive diagonal (DP) directions.
- predictors are composed of arithmetic averages for the chroma data and appropriately scaled Laplacian second-order values for the green data.
- A5N is to be used when the preferred orientation for the interpolation is in the negative diagonal direction within the pixel neighborhood.
- A5P is to be used when the preferred orientation for the interpolation is the positive diagonal direction.
- A5A is used when there is no clear preference for orientation for the interpolation.
- both the green and the chroma data must indicate a minimum of high spatial frequency information for a given orientation to be chosen as the preferred orientation for the interpolation. If there is a large amount of high spatial frequency information in either the green data or chroma data for a given orientation, it will inflate the value of the corresponding classifier value. This, in turn, reduces the likelihood for that orientation to be chosen as the preferred orientation for the interpolation.
- This simplification is achieved by defining the negative diagonal direction as the default preferred orientation for the interpolation when both negative and positive diagonal classifiers are equal.
- the number of occurrences in a typical image when the negative and positive diagonal classifiers are equal is so small that this simplification generally has negligible impact on the image quality of the final reconstructed image.
Abstract
Description
______________________________________ G R G R B G B G G R G R B G B G ______________________________________
______________________________________ A1 G2 A3 G4 A5 G6 A7 G8 A9 ______________________________________
h=|-A3+2A5-A7|+2|G4-G6|+|-G4+2(A5+bh)-G6|
v=|-A1+2A5-A9|+2|G2-G8|+|-G2+2(A5+bv)-G8|
bh=(bh'+A3-G3')/2
bv=(by'+A1-G1')/2
A=(G2+G4+G6+G8)/4
F=(G2+G4+G6+G8)/4+(-A1-A3+4A5-A7-A9)/12
H=(G4+G6)/2+(-A3+2A5-A7)/4
V=(G2+G8)/2+(-A1+2A5-A9)/4
______________________________________ if (h < T1 and v < T1) G5 = A else if (h > T2 and v > T2) G5 = F else if (h < v) G5 = H else G5 = V ______________________________________
______________________________________ G1 G2' G3 G4' G5 G6' G7 G8' G9 ______________________________________
G5"=(G2'+G4'+G6'+G8')/4
G7"=(G1+2G2+2G4+G5+4G7+G9+2G10+2G12+G13)/16
______________________________________ G1 G2 G3' G4 G5 G6' G7 G8' G9 G10 G11' G12 G13 ______________________________________
______________________________________ A1 G2 A3 G4 C5 G6 A7 G8 A9 ______________________________________
A4=(A1+A7)/2+(-G1+2G4-G7)/2
A2=(A1+A3)/2+(-G1+2G2-G3)/2
A5=(A1+A3+A7+A9)/4+(-G1-G3+4G5-G7-G9)/4
DN=|-G1+2G5-G9|+|A1-A9|
DP=|-G3+2G5-G7|+|A3-A7|
A5N=(A1+A9)/2+(-G1+2G5-G9)/2
A5P=(A3+A7)/2+(-G3+2G5-G7)/2
A5A=(A1+A3+A7+A9)/4+(-G1-G3+4G5-G7-G9)/4
______________________________________ if (DN < DP) A5 = A5N else if (DP < DN) A5 = A5P else A5 = A5A ______________________________________
______________________________________ if (DN <= DP) A5 = A5N else A5 = A5P ______________________________________
______________________________________ PARTS LIST ______________________________________ 2input section 4recording section 10exposure section 12image sensor 13color filter array 14 output diode 16 A/D converter 18image buffer 20control processor 22digital signal processor 24removable memory card 26connector 28processing buffer 30display panel 32 green pixelvalue averaging selection 36luminance section 38chroma section 40 selectbest luma interpolation 42 select luma pixel values to average 43 replace selected luma pixel values with average pixel values 44 interpolate missingluma values 46 selectbest chroma interpolation 48 interpolate missingchroma values 50 compute horizontal and vertical composite classifier values 51classifier threshold # 1test 52 select slowly changing scene detail method ofinterpolation 53classifier threshold # 2test 54 select rapidly changing scene detail method ofinterpolation 55classifier equality test 56 select default method forinterpolation 57 select the interpolation method corresponding to thesmaller value 60 horizontalneighboring pixel test 61 selecthorizontal interpolation method 62 vertical neighboringpixel test 63 selectvertical interpolation method 64 compute positive and negative composite classifier values 65classifier equality test 66 select default method forinterpolation 67 select interpolation method corresponding to thesmaller value 70 average red/blue values 72 addgreen correction factor 80 averagegreen value 82 add red/blue correction factors 90 compute horizontal and vertical composite classifier values foradjacent luma pixels 92classifier threshold test 94 select luma pixel value for averaging ______________________________________
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